Caspase3 Intensity - MG132 assay

#install.packages("readxl")
#install.packages("imager")
#devtools::install_bitbucket("graumannlabtools/multipanelfigure")

# install.packages("BiocManager")
# BiocManager::install("EBImage")

#install.packages('readbitmap')

library(ggplot2)
library(dplyr)
library(gapminder)
library(ggthemes)
library("readxl")
library(tidyverse)
library(imager)
library("EBImage")
library(plotly)

Read the excel file

Caspase3 <- read_excel("C:/Users/mdp18pm/Google Drive/Lab book/2021/APRIL 2021/14_April-23_March_Caspase3_DPRs_CorticalNeurons/Plots with R/Results_Caspase3.xlsx")

Caspase3 Fluorescent Intensity

Now we plot a Grouped graph for Caspase3 fluorescent intensity levels

 
# Grouped
p <- Caspase3 %>% 
      ggplot(aes(fill=Treatment, y=Fluo_Int, x=Condition)) + 
      geom_bar(position="dodge", stat = "summary", fun.y = "mean") +   #Use always stat=summary for mean
    labs(x = "", y = "Caspase3_Int", 
              title = "Caspase3 levels") +
    coord_cartesian(ylim = c(195, 230))

Ignoring unknown parameters: fun.y

    #theme(axis.text.x = element_text(angle = 0, vjust = 1, hjust=1))

fig <- ggplotly(p)

No summary function supplied, defaulting to `mean_se()`

fig

Now we plot a Grouped graph for Caspase3 fluorescent intensity levels for just REPLICATE N=1

 
# Grouped
p2 <- Caspase3 %>% 
      filter(Replicate == "n1") %>%     #we only want to look at n=1
      ggplot(aes(fill=Treatment, y=Fluo_Int, x=Condition)) + 
        geom_bar(position="dodge", stat="identity") +
      labs(x = "", y = "Caspase3_Int", 
              title = "Caspase3 levels_ REPLICATE N=1") +
      coord_cartesian(ylim = c(195, 230)) 
      #theme(axis.text.x = element_text(angle = 60, vjust = 1, hjust=1))

fig2 <- ggplotly(p2)

fig2

Now we plot a Grouped graph for Caspase3 fluorescent intensity levels for just REPLICATE N=2

 
# Grouped
p3 <- Caspase3 %>% 
        filter(Replicate == "n2") %>%     #we only want to look at n=1
        ggplot(aes(fill=Treatment, y=Fluo_Int, x=Condition)) + 
          geom_bar(position="dodge", stat="identity") +
        labs(x = "", y = "Caspase3_Int", 
                    title = "Caspase3 levels_ REPLICATE N=2") +
        coord_cartesian(ylim = c(195, 230)) 
        #theme(axis.text.x = element_text(angle = 60, vjust = 1, hjust=1))

fig3 <- ggplotly(p3)

fig3

NA

Now we plot the two replicates side-by-side to facilitate our visualization

 
# Grouped
p4 <- Caspase3 %>% 
      ggplot(aes(fill=Treatment, y=Fluo_Int, x=Condition)) + 
      geom_bar(position="dodge", stat = "summary", fun.y = "mean") +   #Use always stat=summary for mean
    labs(x = "", y = "Caspase3_Int", 
              title = "Caspase3 levels_ Two replicates") +
    coord_cartesian(ylim = c(195, 230)) +
    facet_wrap(~Replicate) +
    theme(axis.text.x = element_text(angle = 60))

Ignoring unknown parameters: fun.y

fig4 <- ggplotly(p4)

No summary function supplied, defaulting to `mean_se()`
No summary function supplied, defaulting to `mean_se()`

fig4

Caspase3 signal_Occupied area

Now we plot a Grouped graph for Caspase3 signal_Occupied area

 
# Grouped
p5 <- Caspase3 %>% 
      ggplot(aes(fill=Treatment, y=Area_of_Signal, x=Condition)) + 
        geom_bar(position="dodge", stat = "summary", fun.y = "mean") +
      labs(x = "", y = "Caspase3_Area of signal", 
                  title = "Caspase3 Area")  

Ignoring unknown parameters: fun.y

      #coord_cartesian(ylim = c(130, 140)) +
      #theme(axis.text.x = element_text(angle = 60, vjust = 1, hjust=1))

fig5 <- ggplotly(p5)

No summary function supplied, defaulting to `mean_se()`

fig5

Now we plot a Grouped graph for Caspase3 signal_Occupied area just for REPLICATE N=1

 
# Grouped
p6<- Caspase3 %>% 
      filter(Replicate == "n1") %>%     #we only want to look at n=1
      ggplot(aes(fill=Treatment, y=Area_of_Signal, x=Condition)) + 
        geom_bar(position="dodge", stat="identity") +
      labs(x = "", y = "Caspase3_Area of signal", 
              title = "Caspase3 Area_ REPLICATE N=1") 
      #coord_cartesian(ylim = c(195, 230)) 
      #theme(axis.text.x = element_text(angle = 60, vjust = 1, hjust=1))

fig6 <- ggplotly(p6)

fig6

NA

Now we plot a Grouped graph for Caspase3 signal_Occupied area just for REPLICATE N=2

 
# Grouped
p7<- Caspase3 %>% 
      filter(Replicate == "n2") %>%     #we only want to look at n=1
      ggplot(aes(fill=Treatment, y=Area_of_Signal, x=Condition)) + 
        geom_bar(position="dodge", stat="identity") +
      labs(x = "", y = "Caspase3_Area of signal", 
              title = "Caspase3 Area_ REPLICATE N=2") 
      #coord_cartesian(ylim = c(195, 230)) 
      #theme(axis.text.x = element_text(angle = 60, vjust = 1, hjust=1))

fig7 <- ggplotly(p7)

fig7

NA

 
# Grouped
p8 <- Caspase3 %>% 
      ggplot(aes(fill=Treatment, y=Area_of_Signal, x=Condition)) + 
        geom_bar(position="dodge", stat = "summary", fun.y = "mean") +
      labs(x = "", y = "Caspase3_Area of signal", 
                  title = "Caspase3 Area_ Two Replicates")  +
      facet_wrap(~Replicate) +
      #coord_cartesian(ylim = c(130, 140)) +
      theme(axis.text.x = element_text(angle = 60, vjust = 1, hjust=1))

Ignoring unknown parameters: fun.y

fig8 <- ggplotly(p8)

No summary function supplied, defaulting to `mean_se()`
No summary function supplied, defaulting to `mean_se()`

fig8

NA